欠定场景下的GNSS欺骗干扰源稀疏测向
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作者单位:

1.哈尔滨工业大学 仪器科学与工程学院;2.中国矿业大学 信息与控制工程学院

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中图分类号:

TN967.1

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国家自然科学基金项目(面上项目,重点项目,重大项目)


Sparse Direction Finding for GNSS Spoofing Source in Underdetermined Scenarios
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    摘要:

    针对传统的子空间类测向算法在欠定场景下失效,且需要信号源数量作为先验信息的问题,提出一种基于互质阵列的GNSS欺骗干扰源测向方法,以提升卫星导航接收机在欺骗环境下的应用安全。该方法通过构建循环相关矩阵以降低噪声对互质阵列信号处理性能的影响,并通过矢量化循环相关矩阵获取虚拟域等效阵列信号。在此基础之上,设计一个基于虚拟域信号稀疏重构的优化问题,通过最小化拟合误差,获得高精度、多自由度测向结果。仿真结果表明,所提算法相比于传统子空间类算法具有更高的测向精度,而且在欠定场景下,依旧可以提供可靠的欺骗源测向结果。

    Abstract:

    Aiming at the problem that the traditional subspace-like direction finding algorithm fails in underdetermined scenarios and requires the number of signal sources as a priori information, a GNSS spoofing source direction finding method based on coprime array is proposed to improve the application security of satellite navigation receivers in spoofing environment. Specifically, we first construct the cyclic correlation matrix to reduce the impact of noise on the performance of the coprime array signal processing, and the virtual domain equivalent array signal is obtained by vectoring the cyclic correlation matrix. On this basis, an optimization problem based on sparse signal reconstruction in virtual domain is designed to achieve high-precision, multi-degree of freedom direction finding for sources by minimizing the fitting error. Finally, the simulation results show that compared with traditional subspace algorithm, the proposed algorithm has higher estimation accuracy, and the direction finding results are still reliable under the case of underdetermined.

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历史
  • 收稿日期:2022-11-20
  • 最后修改日期:2023-04-15
  • 录用日期:2023-04-24
  • 在线发布日期: 2025-02-20
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